This invention relates to a system for determining the range and color of objects within a scene using laser light, and more particularly to improvements therein.
The recognition of three-dimensional objects in a complex cluttered scene by machine, is one of the major goals in present machine intelligence research studies. Many potential applications for industrial automation, and for deep sea and planetary exploration, have been suggested, and await an economic solution.
The general problem of recognizing objects in a cluttered scene is greatly complicated because of various factors. One of these is occlusion wherein only parts of objects may be visible, the remaining parts being hidden from view by parts of other objects. Another problem is caused by shadows, since it is often difficult to discriminate between shadows and the real objects. Other problems are caused by highlight reflections of light from portions of surfaces of an object.
The color of a surface detected by the human eye or a TV color camera depends not only on the material characteristics of the surface viewed, but also on the spectral and spatial distribution characteristics of a light falling on the surface. Although there may be considerable prior knowledge, it is generally true that lighting conditions in a scene are highly variable and unpredictable. Thus, a surface may appear to have a different "color" when viewed under incandescent lamps, fluorescent or daylight lighting; the situation can be even further complicated when multiple sources of light are present, such as in a room illuminated by both artificial and natural light sources, or by several light sources of any kind with different spectral outputs.
The intensity of light falling on every point of the surface of an object is highly variable, depending on the position of each such point relative to the position and spatial distribution of light from each light source. Many picture processing techniques designed to extract relevant features that are based on discontinuities in intensity are plagued with the wide variations and intensity encountered in regions which do not have discontinuities. Thus, it would be advantageous to use a known and controlled light source to provide the light for scanning the scene, eliminating spurious discontinuities. Furthermore, regions in the scene which have no three-dimensional discontinuities, such as planar regions (e.g., wall or floor) can be extracted using range data, even though there may be many colors present in that region. Thus, range data combined with accurate color data can be used to describe surfaces precisely. Such descriptions form the bases of improved recognition systems for objects in cluttered scenes.